Q-omics provides the consensus-scored PFDN4 profile across patient tissues and cancer cell-line models. PFDN4 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, PFDN4 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, PFDN4 protein abundance shows 19,772 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight LIHC, HNSC, and LUAD as cancer lineages where PFDN4 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for PFDN4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PFDN4 survival associations across molecular data types. PFDN4 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PFDN4 RNA expression–survival associations across cancer types. High PFDN4 expression shows unfavorable associations in LIHC, HNSC, KIRP, SCLC, ACC and MESO. The LIHC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify LIHC as the clearest survival context for PFDN4 RNA expression.
This table summarizes PFDN4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PFDN4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PFDN4 shows higher tumor expression in HNSC, KIRC, BLCA, LIHC, LUAD and LUSC. The HNSC box plot shows higher PFDN4 RNA expression in tumor versus normal tissue (log2 FC = +1.078, t-test p < 0.001).
This table shows molecular features associated with PFDN4 in patient tissues and cancer cell lines. In patient samples, PFDN4 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, PFDN4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and UPPER_AERODIGESTIVE_TRACT.
